Big Data in the Age of AI

Introduction

• How big data shapes AI

1. Defining Big Data

• The volume, velocity, and variety of big data
• Artificial intelligence and machine learning
• Social media and the Internet of Things
• Data warehouses, data lakes, and the cloud
• Edge computing and fog computing

2. How Is Big Data Used?

• Big data for business strategy
• Big data for customer interactions
• Big data for applications

3. Big Data and Data Science

• Ten ways big data is different from small data
• The three facets of data science
• Data science without big data
• Big data without data science

4. Ethics in Big Data

• Big data and privacy
• Data governance

5. Data Logistics

• Structured, semi-structured, and unstructured data
• Batch processing vs. stream processing
• Distributed storage and processing
• An evolving data landscape

6. Analyzing Big Data

• Challenges with data preparation
• Visualizing big data
• Data mining
• Text analytics
• Sentiment analysis
• Predictive analytics
• Anomaly detection

Conclusion

• Next steps